Networks are all around us – from social network relationships to transport and communications networks. They capture the links within our world. These networks can be highly dynamic, where participants move around and their relationships to and interactions with other participants change accordingly. It is therefore very important to capture the movement of network nodes through mobility models in order to be able to forecast the future state of the network. Understanding the node mobility, however, is not enough. Consider a disease spreading through the movement of people, such as COVID-19. While understanding how people move is necessary to understand how the disease spreads, there is also a need to understand the process by which the disease spread and how this process interacts with the people movement process. We refer to this as diffusion modelling, which builds on the underlying mobility modelling. This project is concerned with diffusion modelling on highly dynamic networks, to cover diffusion processes ranging from disease spread, the spread of computer viruses, or the diffusion of trust in a network.
The Trusted Networks Lab is collaborating with CSIRO on the Disease Networks and Mobility (DiNeMo) project, which was recently a finalist for the UNSW Eureka Prize for Excellence in Interdisciplinary Scientific Research. The project is also linked to SPARK, a Centre for Research Excellence aimed at strengthening preparedness in the Asia-Pacific region through knowledge, under the ASEAN-Pacific Infectious Disease and Response program (APIDDaR).
Project Team
Prof. Raja Jurdak
Dr. Jess Liebig (CSIRO)
Dr. Dean Paini (CSIRO)
Dr. Kamran Najeebullah (CSIRO)
Ahmad El Shoghri (CSIRO/UNSW)
Prof. Salil Kanhere (UNSW)
A/Prof. Lauren Gardner (Johns Hopkins University)
Dr. Cassie Jansen (QLD Health)
Dr. Md Shahzamal
Dr. Dimitri Perrin
Luz Stefani Sotomayor Valenzuela
Stephen Kim
Recent News
Related Publications
J. Liebig, F. De Hoog, D. Paini, R. Jurdak, Forecasting the probability of local dengue outbreaks in Queensland, Australia, Accepted at Epidemics, November, 2020. (in press)
Shahzamal M, Mans B, Hoog Fd, Paini D, Jurdak R (2020) Vaccination strategies on dynamic networks with indirect transmission links and limited contact information. PLOS ONE 15(11): e0241612. https://doi.org/10.1371/journal.pone.0241612
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Available online at medRxiv: https://doi.org/10.1101/2020.10.11.20211060
A. El Shoghri, J. Liebig, R. Jurdak, L. Gardner, S. Kanhere, “Identifying highly influential travelers for spreading disease on a public transport system,” To appear in proceedings of the 21st IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (IEEE WoWMoM), Cork, Ireland, August, 2020.pdf
Liebig J, Jansen C, Paini D, Gardner L, Jurdak R (2019) A global model for predicting the arrival of imported dengue infections. PLOS ONE 14(12): e0225193. pdf
M. Shahzamal, R. Jurdak, B. Mans, F. De Hoog, Indirect interactions influence contact network structure and diffusion dynamics, Royal Society Open Science, 6:8, August, 2019. DOI: https://doi.org/10.1098/rsos.190845
M. Kim, D. Paini, R. Jurdak, Modeling stochastic processes in disease spread across a heterogeneous social system, Proceedings of the National Academy of Sciences, 116 (2) 401-406, 2019. pdf
A. El Shoghri, J. Liebig, L. Gardner, R. Jurdak, S. Kanhere, “How mobility patterns drive disease spread: A case study using public transit passenger card travel data,” In proceedings of the First International Workshop on Data Distribution in Industrial and Pervasive Internet @ WoWMoM, June, 2019.
M. Kim, D. Paini, R. Jurdak, Real-world diffusion dynamics based on point process approaches: a review, Artificial Intelligence Review, September, 2018. pdf
M. Shahzamal, R. Jurdak. B. Mans, F. De Hoog, “A Graph Model with Indirect Co-location Links,” In proceedings of the 14th International Workshop on Mining and Learning with Graphs, co-located with KDD, London, UK, August, 2018.
M. Shahzamal, R. Jurdak, B. Mans, A. El Shoghri, F. De Hoog, ” Impacts of Indirect Contacts in Emerging Infectious Diseases on Social Networks,” In proceedings of Big Data Analysis for Social Computing @ PAKDD, Melbourne, Australia, June, 2018.
M. Shahzamal, R. Jurdak, R. Arablouei, M. Kim, K. Thilakarathna, B. Mans, “Airborne Disease Propagation on Large Scale Social Contact Network,” In proceedings of the Second International Workshop on Social Sensing (SocialSens), as part of CPSWeek, Pittsburg, USA, April, 2017.
M. Kim, R. Jurdak, “Heterogeneous Social Signals Capturing Real-world Diffusion Processes,” In proceedings of the Second International Workshop on Social Sensing (SocialSens), as part of CPSWeek, Pittsburg, USA, April, 2017.
K. Zhang, R. Arablouei, and R. Jurdak, “Predicting Prevalence of Influenza-Like Illness in Australia From Geo-Tagged Tweets,” In proceedings of the 1st International Workshop on Social Computing (IWSC), as part of the 26th International World Wide Web (WWW) Conference, Perth, Australia, April, 2017.
S. Khan, N. Bergmann, R. Jurdak and B. Kusy, “Mobility in Cities: Comparative Analysis of Mobility Models Using Geo-tagged Tweets in Australia,” In proceedings of the IEEE 2nd International Conference on Big Data Analysis (ICBDA), Bejing, China, March, 2017.
K. Zhao and R. Jurdak, “Understanding the spatiotemporal pattern of grazing cattle movement,” Nature Scientific Reports, 6:31967 EP, August 2016.
Thomas B, Jurdak R, Zhao K, Atkinson I (2016) Diffusion in Colocation Contact Networks: The Impact of Nodal Spatiotemporal Dynamics. PLoS ONE 11(8): e0152624. doi:10.1371/journal. pone.0152624
R. Jurdak, A. Elfes, B. Kusy, A. Tews, W. Hu, E. Hernandez, N. Kottege, P. Sikka, ”Autonomous Surveillance for Biosecurity”, Trends in Biotechnology, 33(4):201-207, April, 2015.
R. Jurdak, K. Zhao, J. Liu, M. AbouJaoude, M. Cameron, D. Newth, “Understanding Human Mobility from Twitter,” PLOS ONE, 10(7): e0131469. doi:10.1371/journal.pone.0131469. July, 2015.
J. Liu, K. Zhao, S. Khan, M. Cameron, R. Jurdak, “Multi-scale Population and Mobility Estimation with Geo-tagged Tweets,” In proceedings of 31st IEEE International Conference on Data Engineering (ICDE) Workshop BioBAD 2015, Seoul Korea, April 2015.
M. Trad, R. Jurdak, and R. Rana, “Guiding Ebola Patients to Suitable Health Facilities: An SMS-based Approach,” F1000 Research 4:43, February 2015.